Abstract

Abstract

Abstract
Palaeoclimate time series, reflecting the state of Earth's climate in the distant past, occasionally display very large and rapid shifts showing abrupt climate variability. The identification and characterisation of these abrupt transitions in palaeoclimate records is of particular interest as this allows for understanding of millennial climate variability and the identification of potential tipping points in the context of current climate change. Methods that are able to characterise these events in an objective and automatic way, in a single time series, or across two proxy records are therefore of particular interest. In our study the matrix profile approach is used to describe Dansgaard-Oeschger (DO) events, abrupt warmings detected in the Greenland ice core, and Northern Hemisphere marine and continental records. The results indicate that canonical events DO-19 and DO-20, occurring at around 72 and 76 ka, are the most similar events over the past 110 000 years. These transitions are characterised by matching transitions corresponding to events DO-1, DO-8, and DO-12. They are abrupt, resulting in a rapid shift to warmer conditions, followed by a gradual return to cold conditions. The joint analysis of the delta 18O and Ca2+ time series indicates that the transition corresponding to the DO-19 event is the most similar event across the two time series.

Abstract
This paper advocates for the integration of system identification in graduate-level control system courses using accessible theoretical tools. Emphasising real-world applications, particularly in Remotely Operated Vehicle (ROV), the study proposes ROV as educational platforms for teaching control principles. As a concrete example, the paper presents a graduation course project focusing on designing a depth control system for an ROV, where students derive the model from experimental data. This practical application not only enhances the students skills in system identification but also prepares them for challenges in controlling complex systems in both academic and industrial settings.

Abstract
The eDNA autonomous biosampler results from a line of research aimed at developing systems for sampling and collecting marine biological data, and for collecting environmental DNA. Environmental DNA is a tool that has been increasingly used in the biological monitoring of aquatic environments, as it is a non-invasive method with very promising results when it comes to assessing biological diversity. In this sense, the automation of this method has the potential to greatly increase the temporal and spatial resolution of current biological monitoring programs in aquatic environments. The system has been developed in a partnership between research teams at the Centre for Robotics and Autonomous Systems (CRAS - INESC TEC) and CIIMAR and has been tested in multiple operational scenarios, including the Arctic, where it was attached to the AUV IRIS.

Abstract
The Czech Republic is home to the Hranice Abyss, the world's deepest natural underwater cave, a site extensively explored by a dedicated team of divers from a speleology group. Over the years, numerous studies have been conducted to unravel the cave's mysteries, delving into fields such as biology, hydrogeology, and geology. Mapping a cave of such vast dimensions and staggering depth poses formidable challenges, making the task hazardous, demanding, and timeintensive for a limited team of divers. In July 2022, the UNEXUP project was invited to explore and map the cave with its robot (UX1-neo), which contains many acoustic and optical sensors, used for navigation, localization, and mapping. Its unique control and dynamics allow the robot to successfully navigate through caves and flooded mines. This paper delves into the specifics of the six days of mission dives, offering insights into the mapping process, and presenting some of the results obtained from the entire cave.